Predicting public company bankruptcies said tougher

With the second-quarter corporate earnings season nearly over, new research from theStanford University Graduate School of Businessexamines the usefulness of financial statement and market data for investors who want to ascertain the likelihood of bankruptcy.

The results of that research aren't completely reassuring.

The authors analyzed 40 years of financial data garnered from thousands of public corporations. They reviewed key financial ratios, such as return on assets and leverage, reported in filings to theU.S. Securities and Exchange Commission, and market-related data such as market capitalization and stock returns.

Over the period they examined1962 to 2002the data became significantly less useful in predicting bankruptcy.

Maureen F. McNichols, professor of public and private management at the Stanford Graduate School of Business, says, "Investors should be concerned and aware of this when they assess bankruptcy risk."

A professor of accounting, McNichols is quick to add that financial statement data are still highly relevant. Of the companies she and her colleagues studied, about 1 percent fell into bankruptcy, and despite the deterioration in financial-statement usefulness, financial ratios and market data are still important tools for predicting insolvency, she says.

Nonetheless, the results are concerning enough that McNichols believes regulators and standards setters such as the U.S. Securities and Exchange Commission and theFinancial Accounting Standards Boardshould be aware of this issue.

Three major factors muddy the waters for investors attempting to predict bankruptcy, the researchers found.

First, during the sample period, there is increasing evidence that management exercises discretion over financial reporting, and there have been increasing numbers of restatements because the financial statements were materially misleading.

Maria Correia, study co-author and assistant professor of accounting at the London Business School, says, "Our findings indicate that the manipulation of reported results gives a misleading impression of profitability and reduces investors' ability to predict bankruptcy."

For example, he cites companies recognizing revenue ahead of schedule or that fraudulently might appear profitable. As a result, the bankruptcy prediction model is much less likely to classify bankrupt companies that also restated earnings accurately, assigning lower risk due to their overstated earnings.

Secondly, many concerns, particularly the technology companies listed on theNasdaq exchange, are heavy spenders on research and development. R&D in itself certainly isn't a cause for concern, but because this "intangible" is not recognized on the balance sheet, it makes various financial ratios and data less useful.

Third, the frequency of companies reporting losses has increased substantially during the past 40 years. Because predicting future earnings for corporations that suffer losses involves substantially greater uncertainty than for companies that are profitable, the bankruptcy prediction model is less likely to classify accurately those companies operating in the red that will go bankrupt.

Consider a corporation that suffers a loss. The fact that it has lost money obviously isn't good news, but a lossin and of itselfdoesn't mean a company will go bankrupt. Losses complicate the financial picture, the researchers found, because while corporations reporting a loss are more likely to go bankrupt on average, it's harder to predict which loss companies will do so compared with firms earning a profit.

In an earlier study that didn't include Nasdaq-listed companies, McNichols and others also found that using both traditional accounting variables and market data led to better predictions than using one or the other type of data. In the new study, researchers find that market data consistently has been useful during the past 40 years, but it hasn't offset the decline over time in informativeness of the financial statements, so the overall ability to predict bankruptcies has declined.

William H. Beaver, a professor emeritus at Stanford's business school, says, "If investors have access to alternative sources of information that compensate for less informative financial statements, the market-based model should reflect this," but that isn't the case.

This is especially true for companies listed on the Nasdaq, which have higher rates of intangibles, greater frequency of losses, and more frequent restatements. For example, the model using financial ratios and market data correctly classifies 91 percent of bankrupt companies in years when those firms had no restatements, but only 68 percent of bankrupt corporations experiencing restatements.

Given these findings, investors should recognize that it may be harder to assess bankruptcy risk.